Analytics-DA-201 Exam Dumps - Salesforce Certified Tableau Data Analyst

There are different ways to prepare the data in Tableau Prep, but one possible answer is:

Answer area:

Join the tables.

Aggregate the data by Sales Team.

Add the following filter to the Employees table: Sale Team - Team Alpha.

 To analyze sales trends over time for every sales team, you need to combine the data from the Orders and Employees tables. You can do this by joining the tables on the Rep ID column, which is a common identifier for both tables. This will create a single table with all the columns from both tables. Next, you need to aggregate the data by Sales Team, which is the level of analysis you want. You can do this by grouping the data by the Sales Team column and applying an aggregation function (such as sum, average, count, etc.) to the other columns that you want to measure (such as Total Amount, Rep Tenure, etc.). This will create a summary table with one row for each sales team and the aggregated values for the other columns. Finally, you need to filter the data to focus on a specific sales team, such as Team Alpha. You can do this by adding a filter to the Employees table and selecting only the rows where Sales Team equals Team Alpha. This will remove the rows for other sales teams and keep only the data for Team Alpha.

In the context of filtering data in Tableau, both string and integer parameters can be used to dynamically filter data. A string parameter can be used to filter text-based values, while an integer parameter is suitable for numerical values. In the provided dataset and result URLs, it appears that a unique identifier or key (which could be a string or integer) is being used to filter specific data entries. References: The information is based on the following sources:

An Introduction to Parameters in Tableau

Create Parameters - Tableau

Data interpreter is a feature that helps you clean and structure your data in Excel before importing it into Tableau. It detects and removes any headers, footers, subtotals, or other elements that are not part of the actual data. It also splits any merged cells and fills in any missing values. In this case, data interpreter provides the following results:

It removes the first three rows and the last two rows that contain headers and footers.

It splits the merged cells in column A and fills in the missing values with “Fiction” or “Non-Fiction”.

It does not remove or change any other rows or cells.

Therefore, the number of rows of data that will be ingested into Tableau as values is 17, which is the number of rows left after removing the headers and footers. References: https://help.tableau.com/current/pro/desktop/en-us/importing_cleaning_up_data.htm https://help.tableau.com/current/pro/desktop/en-us/importing_data_interpreter.htm

Based on the Data Interpreter ' s results and the provided Excel dataset screenshot, the number of rows of data that will be ingested into Tableau as values is 17. The Data Interpreter has identified and excluded headers and footers, and the rows with actual data are considered for analysis.

To modify the bar chart to show the percentage of sales for each Subcategory within every Category, you need to do the following steps:

Open the link to Book1 found on the desktop. This will open the Tableau workbook that contains the CategoryPercentage worksheet.

Click on the CategoryPercentage tab at the bottom of the workbook to open the worksheet. You will see a bar chart that shows the total sales for each Subcategory across all Categories.

Right-click on Sales on the Columns shelf and select Add Table Calculation from the menu. This will open a dialog box that allows you to apply a calculation to your measure.

Select Percent of Total from the Calculation Type drop-down list. This will calculate the percentage of sales for each Subcategory out of the total sales for all Subcategories.

Select Category from the Compute Using drop-down list. This will calculate the percentage of sales for each Subcategory within every Category, instead of across all Categories. The total percentage for every Category will be 100%.

Click OK to apply the table calculation. You will see that the bar chart now shows the percentage of sales for each Subcategory within every Category.